behavioral/systems/cognitive ... · flies were individually placed into 5 65 mm ... five flies aged...

Behavioral/Systems/Cognitive

Identifying Sleep Regulatory Genes Using a DrosophilaModel of Insomnia

Laurent Seugnet,1 Yasuko Suzuki,1 Matthew Thimgan,1 Jeff Donlea,1 Sarah I. Gimbel,2 Laura Gottschalk,1

Steve P. Duntley,3 and Paul J. Shaw1

1Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, Missouri 63110, 2Neuroscience Program, University ofCalifornia, San Diego, San Diego, California 92093, and 3Department of Neurology, Washington University Sleep Medicine Center, St. Louis, Missouri 63108

Although it is widely accepted that sleep must serve an essential biological function, little is known about molecules that underlie sleepregulation. Given that insomnia is a common sleep disorder that disrupts the ability to initiate and maintain restorative sleep, a betterunderstanding of its molecular underpinning may provide crucial insights into sleep regulatory processes. Thus, we created a line of fliesusing laboratory selection that share traits with human insomnia. After 60 generations, insomnia-like (ins-l) flies sleep 60 min a day,exhibit difficulty initiating sleep, difficulty maintaining sleep, and show evidence of daytime cognitive impairment. ins-l flies are alsohyperactive and hyperresponsive to environmental perturbations. In addition, they have difficulty maintaining their balance, haveelevated levels of dopamine, are short-lived, and show increased levels of triglycerides, cholesterol, and free fatty acids. Although theircore molecular clock remains intact, ins-l flies lose their ability to sleep when placed into constant darkness. Whole-genome profilingidentified genes that are modified in ins-l flies. Among those differentially expressed transcripts, genes involved in metabolism, neuronalactivity, and sensory perception constituted over-represented categories. We demonstrate that two of these genes are upregulated inhuman subjects after acute sleep deprivation. Together, these data indicate that the ins-l flies are a useful tool that can be used to identifymolecules important for sleep regulation and may provide insights into both the causes and long-term consequences of insomnia.

IntroductionSleep has been observed in all mammals, birds, reptiles, and in-vertebrates in which it has been thoroughly investigated (Shawand Franken, 2003; Allada and Siegel, 2008). In mammals, sleep isnot regulated from a single brain center or by a solitary neuro-transmitter (Saper et al., 2005). Rather, sleep is modulated by avariety of neurochemicals operating through multiple neuronalsystems distributed throughout the neuraxis (Borbely and To-bler, 1989; Obal and Krueger, 2003). Given the complexity ofsleep regulation, it is not surprising that sleep disorders are highlyprevalent in the general population. Although sleep disorders arebelieved to have a strong genetic component, it is rare for thesedisorders to be attributed to single gene defects (Tafti et al., 2005).Thus, sleep is a complex behavior that is regulated by many genesand their interactions.

This principle of a distributed sleep regulatory network alsoappears to be true for the genetic model organism Drosophilamelanogaster (Joiner et al., 2006; Pitman et al., 2006; Foltenyi et

al., 2007; Sheeba et al., 2008). Moreover, sleep in flies is alsoinfluenced by a variety of molecular pathways (Shaw et al., 2002;Andretic and Shaw, 2005; Cirelli et al., 2005; Kume et al., 2005;Foltenyi et al., 2007; Koh et al., 2008). Interestingly, a closer in-spection of large populations of wild-type flies reveals that manyindividuals display disrupted sleep (Andretic and Shaw, 2005;Seugnet et al., 2008). As with humans, it is likely that the changesin sleep regulation observed in these individuals is attributable tomodifications in many genes which may also increase the vulner-ability of these individuals to sleep disruption (e.g., gene � envi-ronment interactions). Thus, populations of wild-type flies nat-urally possess sufficient genetic variability to induce complexsleep phenotypes.

Recently, several labs have used laboratory selection as an ef-ficient strategy to identify genes that underlie complex behavior(Dierick and Greenspan, 2006; Edwards et al., 2006; Sørensen etal., 2007). Given that insomnia is a highly prevalent, naturallyoccurring condition that disrupts the ability to initiate and main-tain restorative sleep, a better understanding of its molecularunderpinning may provide crucial insights into sleep regulatoryprocesses. Thus, we have used laboratory selection to create aunique line of flies that share many traits with human insomniaand have identified genes that are both important for sleep regu-lation and may provide insights into the causes and long-termconsequences of insomnia.

Materials and MethodsFly stocks, sleep monitoring, and sleep deprivation. Canton-S (Cs) flies wereobtained from the Bloomington Drosophila stock center. Insomnia-like

Received Nov. 25, 2008; revised April 1, 2009; accepted April 13, 2009.This study was funded in part by National Institutes of Health Grants 1 R01 NS051305-01A1 and 5 K07 AG21164-

02, the McDonnell Center for Cellular and Molecular Neurobiology, and the National Institutes of Health Neuro-science Blueprint Core Grant (NS057105). We thank Isabelle Raymond Shaw and Anne Germaine for helpful com-ments. L.S. designed the research, performed research, analyzed data, and wrote this manuscript; Y.S., L.G., S.I.G.,and S.P.D. all performed research. M.T. performed research and wrote this manuscript. P.J.S. designed the research,performed research, analyzed data, and wrote this manuscript. All authors commented on this manuscript.

Correspondence should be addressed to Dr. Paul J. Shaw, Department of Anatomy and Neurobiology, Washing-ton University School of Medicine, 660 South Euclid Avenue, Campus Box 8108, St. Louis, MO 63110. E-mail:[email protected].

DOI:10.1523/JNEUROSCI.5629-08.2009Copyright © 2009 Society for Neuroscience 0270-6474/09/297148-10$15.00/0

7148 • The Journal of Neuroscience, June 3, 2009 • 29(22):7148 –7157

(ins-l ) flies used for behavioral and molecular evaluation were obtainedfrom generation 65 to 85 of the selection. Flies were cultured at 25°C,50 – 60% humidity, in a 12 h light/dark (LD) cycle, on a standard foodcontaining yeast, dark corn syrup, molasses, dextrose, and agar. Newlyeclosed female adult flies were collected from culture vials daily underCO2 anesthesia. Three-day-old flies were then individually placed into 65mm glass tubes so that sleep parameters could be continuously evaluatedusing the Trikinetics activity monitoring system as described previously(Shaw et al., 2000). Flies were sleep deprived using an automated sleepdeprivation apparatus that has been found to produce waking withoutnonspecifically activating stress responses (Shaw et al., 2002). The SleepNullifying Apparatus (SNAP) tilts asymmetrically from �60° to �60°,such that sleeping flies are displaced during the downward movement sixtimes per minute. This stimulus is effective presumably because it ini-tiates a geotactic response. The SNAP effectively eliminates all sleep(Shaw et al., 2000). Thus, 100% of the sleep that would normally occurduring stimulation is abolished. Flies were sleep deprived using the SNAPfrom zeitgeber time (ZT) 12 (beginning of the dark phase) to ZT0 (be-ginning of the light phase). Unless otherwise stated, at least 32 flies wereanalyzed for each experimental condition. Differences in sleep time wereassessed using either a Student’s t test or ANOVA which were followed byplanned pairwise comparisons with a Tukey correction.

Locomotor rhythms. Flies were individually placed into 5 � 65 mmtubes with regular food and placed into constant conditions for 10 d.Locomotor activity was continuously recorded in 30 min bins using theTrikinetics system. Locomotor rhythms were analyzed for 6 or 9 d usingMATLAB-based computational tools designed by Joel Levine (Levine etal., 2002). Flies that did not show a significant peak on the periodogramwere considered arrhythmic. At least 30 flies were analyzed for eachgenotype.

Falls. Five flies aged 4 –5 d and placed in 5 � 65 mm tubes weresimultaneously observed by one experimenter during 30 min. Experi-menters were blind to the condition. Data obtained with two differentexperimenters and two generations of ins-l flies were similar and pooledfor the analysis.

Learning. Learning was evaluated using aversive phototaxic suppres-sion (APS) (Le Bourg and Buecher, 2002). Flies are individually tested ina T-maze where they are allowed to choose between a dark and a lightedvial. Adult flies are phototaxic and choose the lighted alley in the absenceof reinforcer. During the test, a filter paper soaked with a quinine solu-tion is placed in the lighted vial to provide an aversive association. In thecourse of 16 trials through the maze, flies learn to make more frequentchoices to the dark vial (photonegative choices). The number of pho-tonegative choices is tabulated during four successive blocks of four tri-als, and the performance score is the percentage of photonegative choicesmade in the last block of four trials. At least eight flies were evaluated foreach condition. For each experiment, learning was evaluated by the sameexperimenter who was blind to genotype and condition. All flies weretested in the morning between ZT0 and ZT4. Flies were sleep deprivedusing the SNAP from ZT12 (beginning of the dark period) to ZT0 (be-ginning of the light period) and until each fly was tested for learning.Learning scores are normally distributed (Seugnet et al., 2008). Differ-ences between scores were assessed using either a Student’s t test orANOVA which were followed by planned pairwise comparisons with aTukey correction. Photosensitivity was evaluated using the T-maze withno filter paper. The average proportion of choices to the lighted vialduring 10 trials was calculated for each individual fly. The phototaxisindex (PI) is the average of the scores obtained for at least five flies�SEM. Sensitivity to quinine/humidity was evaluated as in Le Bourg andC. Buecher (2002) with the following modifications: each fly was indi-vidually placed in a 14 cm transparent cylindrical tube covered with filterpaper, uniformly lighted, and maintained horizontal. In one-half of theapparatus, the filter paper is soaked with quinine solution, whereas theother half is kept dry. The quinine/humidity sensitivity index [referred toas quinine sensitivity index (QSI)] was determined by calculating thetime in seconds that the fly spent on the dry side of the tube when theother side had been wetted with quinine during a 5 min period.

Lifespan. Three-day-old flies were individually placed into 5 � 65 mmtubes, and sleep was monitored until death. Food was replaced every 4 d.

Three independent groups of 30 flies were analyzed for each genotype.Similar results were obtained by aging three groups of 10 flies in regularvials and visually monitoring dead flies every day.

Stress resistance. Three-day-old flies were placed in 5 � 65 mm tubesfor 2 baseline days and then placed in empty tubes (desiccation) or tubeswith 1% agar (starvation) at ZT2, and locomotor activity was monitoreduntil all flies died. Three independent groups of 30 flies were analyzed foreach genotype.

Arousal. To evaluate arousal during the day, Cs and ins-l flies weretransferred in groups of 10 to an empty vial. All flies were awake bothbefore and after the transfer. The vial was then subjected to a rapid shockto induce geotaxis. The percentage of flies present in the top half of a 50ml tube was calculated after 5, 10, 15, 30, 60, and 120 s. To evaluateresponsivity during the flies primary sleep period, we exposed Cs andins-l flies to a 1 min pulse of light at ZT15; flies that were awake did notcontribute to the score. The level of light was sufficiently strong toawaken all animals. The amount of sleep was then calculated for thefollowing hour and expressed as a percentage of baseline sleep.

HPLC. For each condition, independent sets of 20 fly heads (n � 4replicates) were frozen and collected at age 5– 6 d and at ZT0. Sampleswere sent to Dr. Raymond F. Johnson, Neurochemistry Core Laboratory,Nashville, TN, for HPLC analyses.

Lipid analysis. Whole flies (10 –15) were collected for each condition(ZT0). Samples were frozen at �80°C and homogenized in a 2:1 meth-anol:chloroform solution for lipid extraction. Lipid content was evalu-ated using colorimetric assays according to kit manufacturer’s instruc-tions. Triglycerides and cholesterol were evaluated with the Infinity kit(Thermo Electron), and nonesterified free fatty acids with the non-esterified fatty acids C kit (Wako). Lipid measurements were normalizedto the initial weight of the flies (n � 3 replicates).

Quantitative PCR. Total RNA was isolated from sets of 20 fly headswith Trizol (Invitrogen) and DNase I digested. cDNA synthesis was per-formed in quadruplicate using superscript III (Invitrogen), according tomanufacturer protocol. To evaluate the efficiency of each reverse tran-scription, equal amounts of cDNA were used as a starting material toamplify RP49, a gene which expression is not changing during sleepdeprivation (Shaw et al., 2002; Seugnet et al., 2008). cDNA from compa-rable reverse transcription reactions were pooled and used as a startingmaterial to run four quantitative PCR (QPCR) replicates. Expressionvalues for RP49 were used to normalize results between groups.

Microarray gene profiling. Three groups of 20 short-sleeping ins-l flies(criteria, total daily sleep �60 min; daily sleep average, 16 � 5 min) andthree groups of Cs flies (daily sleep average, 725 � 5 min) were collectedat age 5– 6 d. Total RNA was extracted from whole heads using the Trizolprotocol (Invitrogen) and processed for cDNA synthesis and cRNA am-plification according to the Affymetrix protocol. Over-represented geneontology (GO) categories were identified using the GOToolBox software(Martin et al., 2004) with the hypergeometric statistical method. Thefollowing criteria were used to select over-represented GO categoriesshown in Figure 5A: (1) a representation increased at least twofold in theexperimental set compared with the reference; (2) at least 20 genespresent in the given category in the experimental data set; and (3) over-represented with a p � 0.01 after false discovery rate correction.

Human samples. Nine healthy human adult volunteers (seven men andtwo women) were enrolled in the study after providing their consent. Thesleep protocol was performed at the Sleep Medicine Center, Departmentof Neurology, Washington University School of Medicine, and was ap-proved by the Institutional Review Board at Washington UniversitySchool of Medicine. The subjects were randomly separated in twogroups, which where scheduled to alternate two weekends of either nor-mal sleep or 28 h of continuous waking. On the normal-sleep weekend,the volunteers were allowed to fall asleep at 10:00 P.M. Normal sleeparchitecture was confirmed by standard polysomnography. The SDgroup remained awake and was allowed ad libitum access to water duringthe night. Saliva was collected from plain (noncitric acid) cottonSalivettes (Sarstedt), rapidly frozen over dry ice, and kept at �80°C untilassayed. RNA was isolated from cell-free supernatant and processed forQPCR as described previously (Seugnet et al., 2006). Control experi-ments removing either mRNA or reverse transcriptase from the reaction

Seugnet et al. • A Drosophila Model of Insomnia J. Neurosci., June 3, 2009 • 29(22):7148 –7157 • 7149

failed to result in amplification (data notshown), indicating that the signal was mRNAand not attributable to contamination. Resultswere evaluated using the Wilcoxon signed ranktest.

ResultsIsolation of flies presenting insomnia-like traits using laboratory selectionEvaluation of a normative dataset of wild-type Cs flies indicates that they display asufficient range of sleep times and activitylevels to make them suitable for laboratoryselection (Fig. 1A, black bars). In humans,insomnia starting earlier in life is believedto be under greater genetic influence thaninsomnia that is associated with aging(Watson et al., 2006). Thus, sleep was eval-uated in 3-d-old male and female Cs fliesfor 4 d according to standard protocols(Shaw et al., 2000). For each generation,we identified 8 –12 individual male and fe-male flies that simultaneously demon-strated reduced sleep time in combinationwith increased sleep latency, reduced sleepbout duration, and elevated levels of wak-ing activity (ins-l flies). These flies werethen bred over successive generations. Asseen in Figure 1, B and C, total sleep timewas progressively reduced during selectionand stabilized after �30 generations. Al-though sleep time was reduced both dur-ing the day and night, the increase in totalwake time in selected flies came primarilyat the expense of night time sleep (Fig. 1C).Although total sleep time averaged 100min or less by generation 65 (Fig. 1D), �50% of ins-l flies ob-tained �60 min of sleep in a day. Moreover, the distribution ofsleep times was shifted dramatically to the left (Fig. 1A, whitebars). Direct observation of 14 h of fly behavior revealed that allthe ins-l flies were indeed awake and active with very few episodesof quiescence (see also supplemental Video1, available at www.jneurosci.org as supplemental material, for a comparison of ins-land Cs flies).

In humans, primary insomnia is a chronic condition that maypersist for 10 years (Janson et al., 2001). Thus, we evaluated sleepin ins-l flies over their lifespan. Sleep remains disturbed in ins-lflies over time (Fig. 1E). Total sleep for three representative ins-lflies and one Cs fly are shown in Figure 1E. These three ins-l fliesobtained a total of 358 � 128 min of sleep during their first 20 dof life versus 17,567 � 655 min over the same time period in Csflies. Importantly, the shortest-sleeping ins-l flies do not becomelonger sleepers or vice versa. To assay for dominant effects, weevaluated sleep in heterozygous ins-l/� flies and found an inter-mediate sleep phenotype indicating the effects are semidominant(Fig. 1F).

In addition to selecting for short-sleeping flies, we also se-lected for flies with an increased sleep latency, disrupted sleepconsolidation, and hyperactivity. As seen in Figure 2A, ins-l fliesshow increased latency from lights off to the first sleep bout of thenight, suggesting that they have difficulty initiating sleep (An-dretic and Shaw, 2005). ins-l flies also have difficulties maintain-ing sleep as evidenced by an inability to consolidate sleep into

long bouts (Fig. 2B, average sleep bout duration) (Andretic andShaw, 2005). Indeed, the maximum episode of consolidated sleepthat can be generated by an ins-l fly is only 36 � 9 min versus257 � 22 min in Cs flies. Although ins-l flies exhibit fragmentedsleep, they do not compensate by initiating more sleep episodes(6.8 � 0.8 bouts vs 10.4 � 0.2 bouts for ins-l and Cs flies, respec-tively). Since ins-l flies do not compensate by initiating moresleep episodes, it is possible that they are simply short-sleeperswith a reduced need for sleep. Interestingly, ins-l flies exhibit anormal homeostatic response after 12 h of sleep deprivation, in-dicating that they are able to compensate for acute sleep loss (Fig.2C). However, human insomniacs also respond to acute sleeploss (Pigeon and Perlis, 2006), and thus, homeostasis cannot dis-tinguish between short-sleep and insomnia. In humans, insom-nia is associated with increased daytime sleepiness (Edinger et al.,2008). To determine whether ins-l flies also exhibit daytimesleepiness, we evaluated Amylase transcript levels using real-timeQPCR. We have shown that, in flies, Amylase levels are only ele-vated after waking conditions that are associated with increasedsleep drive and are not induced by stress (Seugnet et al., 2006).RNA was extracted from whole heads of Cs and ins-l flies that hadbeen spontaneously awake for 3 h between ZT0 and ZT3. As seenin Figure 2D, ins-l flies show elevated levels of Amylase mRNArelative to Cs flies, suggesting that they may experience increasedsleep drive during their primary wake period.

As mentioned above, patients with insomnia are believed to behyperaroused. Thus, we selected for flies with increased locomo-

Figure 1. Sleep patterns of ins-l flies over generations. A, Frequency distribution of total sleep time in 60 min bins in wild-typeCs flies (n � 1000) and in ins-l flies at generation 65 (n � 364). B, Total sleep time in males (n � 40) and females (n � 40) forsuccessive generations of ins-l flies. C, Daily sleep patterns (min/h) for progressive generations of ins-l flies (n � 32/generation).D, Sleep in minutes per hour for 24 h in Cs (n �32) and ins-l (generation 65; n �32) flies. E, Daily total sleep time is shown for 37 din one Cs and three ins-l flies. F, Daily total sleep time is decreased in ins-l/ins-l as well as in ins-l/Cs flies compared with Cs (ANOVA,F(1,89) � 5.50E � 06, p � � 0.0005). Error bars represent SEM.

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tor activity during waking. As seen in Figure 2E, our selectionprocedure significantly increased the intensity of waking loco-motor activity. The levels of activity during waking in ins-l fliesare high during the day and during the night, and these levels arenot statistically different ( p � 0.56, paired t test). Insomniacs alsoshow greater reactivity to stressors (Drake et al., 2008). To deter-mine whether this would be true for ins-l flies as well, we exposedthem to environmental perturbation during both the day and thenight. As seen in Figure 2F, ins-l flies are more responsive than Csflies to mechanical stimulation during the day. ins-l flies are alsomore responsive to perturbations at night. When Cs and ins-l flieswere exposed to a 1 min light pulse during their primary sleepperiod at ZT15, Cs flies briefly woke up in response to the lightpulse but quickly went back to sleep (12.2 � 9% of sleep lostduring the following hour). In contrast, all the ins-l flies woke upand remained awake for an entire hour (100% of sleep lost, n �16 flies per group, p � 0.05). Together, these data suggest thatins-l flies are in a state of increased arousal.

Physiological changes associated withthe insomnia-like phenotypeTo be considered an insomniac, an indi-vidual must display daytime impairmentor distress in combination with sleep dis-ruption. Human insomniacs report thatthey have impaired concentration andpoor memory (Orff et al., 2007). Thus, weevaluated learning in ins-l flies using APS(Le Bourg and Buecher, 2002). In this task,flies learn to avoid a light that is pairedwith an aversive stimulus (quinine/hu-midity). We have recently shown that APSis sensitive to both sleep loss and sleepfragmentation (Seugnet et al., 2008). Asseen in Figure 3A, learning is significantlyimpaired in the shortest-sleeping ins-lshort

flies compared with Cs controls. To deter-mine whether our selection protocol gen-erated poor-learning flies as an indepen-dent phenotype from the observed sleepdeficit, we evaluated learning in long-sleeping ins-l flies (ins-llong) (Fig. 1A). Im-portantly, longer-sleeping siblings main-tain their ability to learn, indicating thatour selection procedure did not inadver-tently create a poor-learning fly. The timeto complete the test, photosensitivity, andquinine sensitivity (control metrics) weresimilar in Cs, ins-lshort, and ins-llong flies,indicating that the learning deficit was notattributable to differences in sensorythresholds (Fig. 3B; supplemental Table 1,available at www.jneurosci.org as supple-mental material).

In addition to cognitive impairments,human insomniacs exhibit deficits in mo-tor coordination as indicated by difficultyin maintaining their balance (Hauri,1997). Thus, we evaluated the number ofspontaneous falls in young age-matchedCs and ins-l flies walking for 30 min in anobstacle-free environment. Cs flies rarelyfall under these conditions. In contrast,ins-l flies frequently lose their balance (Fig.

3C). Given the role of dopamine in learning and motor control,we evaluated transmitter levels in whole heads of ins-l flies. Asseen in Figure 3D, dopamine levels are significantly elevated inins-l flies (Fig. 3D). Dopamine is present in the brain as well as inperipheral tissues such as the epidermis where it affects pigmen-tation. However, no obvious change in cuticle pigmentation isobserved in ins-l flies. Thus, the large increase in dopamine levelseen in ins-l flies most likely reflects a significant change of theneurotransmitter in the brain. Interestingly, we found that learn-ing impairments after acute sleep deprivation are also associatedwith an increase in dopamine levels (Seugnet et al., 2008). Levelsof 5-HT and GABA, which are also associated with learning andsleep disruption, were not changed (Fig. 3E,F). Together, theseresults further implicate dopamine signaling in cognitive impair-ments after sleep disruption.

Accumulating evidence in humans indicates that sleep disrup-tion may increase the risk of obesity (Knutson and Van Cauter,2008). Moreover, insomnia is more frequent in obese than nono-

Figure 2. Characterization of insomnia-like traits. A, Sleep latency is increased in ins-l flies (n � 28) versus Cs flies (n � 33;*p � 8.78 � 10�8, one-tailed t test). B, Average sleep bout duration is reduced during the dark period in ins-l (n � 32) versusCs (n�32) flies; ANOVA F(1,122) �4.34�104, p�0.0005, *p�0.05 planned comparison with Tukey correction). C, Cumulativesleep lost or gained during 12 h of sleep deprivation and subsequent recovery in ins-l (n � 32) and Cs (n � 32) flies; striped barindicates sleep deprivation. For each hour, the amount of sleep obtained during baseline is subtracted from the respectiveamount of sleep time obtained during the corresponding hour of the sleep deprivation and recovery days; the differencescores are then summed across each hour to create the cumulated gained-lost plot. A negative slope indicates sleep lost,a positive slope indicates sleep gained; when the slope is zero, recovery is complete. D, Amylase mRNA levels are elevatedin ins-l flies (percentage of Cs expression) at ZT0 –1 ( p � 0.0002, one-sample t test). E, Intensity of locomotor activity asmeasured by the counts/waking minutes for 24 h in Cs flies (n � 57) and ins-l flies (n � 61; *p � 1.67 � 10�10, two-tailed ttest). F, Geotaxic response to a sudden shock is greater in ins-l versus Cs flies. Percentage of flies present in the top half of a 50 mltube (responders). Three groups of 10 flies were tested for each genotype (genotype � time interaction, F(6,24) � 4.301, p �0.0006). Error bars represent SEM.


bese individuals (Janson et al., 2001), andcommon genetic effects have been ob-served between insomnia and obesity in arecent twin study (Watson et al., 2006).Thus, we evaluated organismal levels oftriglycerides, free fatty acids, and choles-terol in ins-l flies. As with humans, ins-lflies exhibit increased adiposity (Fig. 3G–I). These data further suggest that ins-lflies are getting less sleep than they needand are not simply short sleepers.

Several recent epidemiological studieshave found that sleep duration and insom-nia are associated with an increased risk ofall-cause mortality and reduced lifespan(Tamakoshi and Ohno, 2004). Reducedsleep has also been associated with short-ened lifespan in Drosophila (Cirelli et al.,2005; Pitman et al., 2006; Koh et al., 2008).If our selected lines are getting less sleepthan they need, one would predict thatthey would have a shortened lifespan. Asseen in Figure 3J, this is indeed the case.The reduced lifespan observed in our ins-lflies may be attributable to reduced sleepor decreased fitness resulting from in-breeding. To determine whether our ins-lflies exhibited reduced fitness, we exposedthem to starvation, desiccation, and para-quat (Fig. 3K,L, paraquat data notshown). Survival curves clearly indicatethat ins-l flies do not exhibit reduced fit-ness when compared with Cs controls. Inaddition, ins-l flies have no discernablemorphological, developmental, or fertilityphenotypes, further indicating that theydo not exhibit reduced fitness.

Sleep in the absence of zeitgebersThe misalignment of sleep and circadiancycles can trigger or aggravate insomniasymptoms in humans (e.g., jet lag). Toassess the influence of zeitgebers, weevaluated sleep in ins-l flies placed intoconstant darkness (DD). When zeitge-bers are removed, ins-l flies show a fur-ther decrease in sleep time (Fig. 4 A, white circles), a result notobserved in Cs flies (Fig. 4 A, black diamonds). To determinewhether the increased wakefulness was attributable to the ab-sence of light, we placed ins-l flies in constant darkness butallowed temperature to maintain a circadian oscillation of�1.0°C. ins-l flies were able to entrain to these small circadianfluctuations in temperature, and sleep was not altered com-pared with LD (Fig. 4 B). To further evaluate the consequencesof sleep loss induced by removing zeitgebers, we evaluated thebehavior of longer-sleeping ins-l flies. Longer-sleeping ins-lflies were examined to ensure that all flies would have theopportunity to lose sleep when placed into DD. Moreover,since the shortest-sleeping ins-l flies cannot learn, it is notpossible to assess whether additional sleep disruption alterscognitive behavior. As seen in Figure 4C, ins-l flies not onlylose sleep when placed into DD for 24 h, they initiate a homeo-static response when placed back into LD. In comparison, Cs

flies only lose 7 � 1% of their baseline sleep in DD. Interest-ingly, Amylase mRNA levels are lower in ins-llong flies com-pared with their short-sleeping siblings when maintained inLD, suggesting that they experience lower sleep drive (Fig. 4 D,left). However, when sleep is disrupted by placing ins-llong fliesinto DD Amylase, mRNA levels increase in comparison withcontrol ins-llong siblings maintained under LD (Fig. 4 D, right).Given the mild-nature of placing flies into constant darkness,these data are consistent with our previous results, demon-strating that, in flies, Amylase levels are responsive to condi-tions of high sleep drive, do not depend on the method used tokeep the animal awake, and are not simply activated by stress.To determine whether waking induced by removing zeitgeberswas associated with learning impairments, we evaluated ins-llong flies under LD and after 5 d in DD. As seen in Figure 4 E,ins-llong flies learn normally under LD but are significantlyimpaired after the additional sleep disruption induced by re-

Figure 3. Physiological changes associated with the insomnia-like phenotype. A, Learning in Cs flies, longer-sleeping ins-l flies(average daily sleep time, 347 � 55 min), and short-sleeping ins-l flies (average daily sleep, 26 � 7 min; n � 10 for each group;*ANOVA, F(1,27) � 10.26, p � 0.0005, *p � 0.05, planned comparison with Tukey correction). B, PI and QSI in Cs flies (n � 5) andshort-sleeping ins-l flies (n � 5). C, Number of falls during 30 min in Cs (n � 20) and ins-l flies (n � 18; *p � 0.0001, two-tailedt test). D–F, Head neurotransmitter levels in Cs and ins-l flies, as measured by HPLC (n � 4 replicates of 20 heads; *p � 0.02,two-tailed t test). G–I, Whole-body lipid content in Cs and ins-l flies (n � 3 replicates of 10 flies): triglycerides (G), free fatty acids(H ), and cholesterol (I ) [*p �0.0001 (G), p �0.002 (H ), p �0.01 (I ), two-tailed t test]. J, Representative survival curve of agingins-l compared with Cs flies (30 flies/group). K, L, Representative survival curves of ins-l and Cs flies after exposure to desiccation(K ) or starvation (L) (30 flies/group). D, Error bars represent SEM.


moving zeitgebers; learning impairments were not associatedwith changes in control metrics (supplemental Table 1, avail-able at www.jneurosci.org as supplemental material), and 5 dof DD does not alter learning in Cs flies (data not shown).Thus, the absence of zeitgebers appears to interfere with theability to obtain needed sleep in ins-l flies.

Is sleep loss in DD associated with a deficit in the circadianpacemaker? Seventy percent of ins-l flies appear to lose locomotorrhythms in constant conditions, whereas the remaining cyclingflies have a normal 24 h period (Fig. 4F). The average rhythmicityindex (RI) was 0.10 � 0.02 for ins-l flies for 9 d in DD, comparedwith 0.43 � 0.03 for Cs flies. We found that RI was not correlatedwith either counts/waking minutes (r � 0.04, n � 30) or theamount locomotor activity (r � �0.2, n � 30). In Drosophila,circadian rhythms in DD are controlled by a subset of clock neu-rons, the small ventral lateral neurons (sLNvs). In ins-l flies, sLNvsneurons still display circadian oscillations of the Period (PER)protein, similar to Cs flies (Fig. 4G). Normal circadian oscilla-tions of the TIMELESS (TIM) protein were also observed in the

sLNvs of ins-l flies: TIM was detected in the cytoplasm at CT18, inthe nucleus at CT0, and was not detected at CT6 and CT12 (datanot shown). These results suggest that the sleep reduction andloss of rhythmicity observed in ins-l flies in constant conditions isnot merely linked to a deficit of the core molecular clock.

Gene profiling of ins-l fliesBy using laboratory selection, we generated a line of flies thatexhibit a constellation of unique phenotypes that may be usefulfor both elucidating molecular mechanisms important for as-pects of sleep regulation and that may provide insights into boththe causes and long-term consequences of insomnia. However, ifthe behavioral changes seen in ins-l flies are caused by changes inmany genes, as is the case for other complex traits, it may not bepossible to easily map them using classic genetic strategies. More-over, since polymorphisms in regulatory regions alter expressionlevels without disrupting gene function (Mackay, 2004), se-quencing strategies may also prove ineffective. Thus, we con-ducted whole-genome transcript profiling using Affymetrix high

Figure 4. Sleep in the absence of zeitgebers. A, Baseline sleep in minutes per hour in Cs and ins-l flies maintained under LD and after placement into DD (arrow). Black rectangle indicates lightsoff. B, Top graph, Sleep in minutes per hour in ins-l flies maintained in LD or in DD. Bottom graph, Circadian oscillations in temperature used to entrain the flies in DD. C, Sleep was evaluated in Cs andins-l flies placed into DD for 24 h (black bars) and then into LD for recovery (white bars). Sleep is expressed as a percentage of baseline sleep in LD. D, Amylase levels in ins-llong flies under LD (n �20) and after 24 h in DD (n � 20); data are presented as percentage change from age-matched ins-lshort and ins-llong flies, respectively (*p � 0.05, two-tailed t test). E, Learning in ins-llong flies inLD (average daily sleep 331 � 19 min) and after 5 d in DD (average daily sleep at DD5, 72 � 14 min; n � 10/group; *p � 0.036, one-tailed t test). F, Representative actograms for single femaleflies from DD1 to DD5 are shown. Similar results were obtained with ins-l males. G, Immunolocalization of PER protein in the sLNvs at DD5 (single confocal sections are shown). Ten brains wereevaluated for each time point; a representative example is shown. Error bars represent SEM.


density oligonucleotide microarrays toidentify genes that are modified in ins-lflies. To maximize the comparison be-tween ins-l and Cs flies and to reduce vari-ability, we monitored sleep for 3 d andidentified individuals that displayed stablesleep patterns. Only those ins-l flies thatslept �60 min a day for each of the 3 dwere included in the study (average dailysleep, 16 � 5 min). Cs flies display a largerange of sleep times (Fig. 1A). To avoidcombining Cs flies with short, fragmentedsleep or flies that displayed excessivelylong sleep and thus might be unhealthytogether with normal-sleeping healthyflies, we identified individuals whose totalsleep fell at the center of the distribution ofdaily sleep (average daily sleep, 721 � 5min). Sleep was evaluated in three inde-pendent groups of ins-l and Cs flies on sep-arate days. RNA was collected from wholeheads of flies that had been spontaneouslyawake for 3 h at CT3; 3 h of spontaneouswaking is sufficient to change gene expres-sion in rodents and flies (Shaw et al., 2000;Cirelli et al., 2004). Statistical differenceswere identified first using the Cyber-TBayesian statistical framework followed byBonferroni correction (http://cybert.mi-croarray.ics.uci.edu/) (Baldi and Long,2001). In addition, the data were indepen-dently analyzed using Partek GenomicsSuite with a false discovery rate test correc-tion set to p � 0.01 (Partek). Only thosegenes that were identified as being signifi-cant using both Cyber-T and Partek wereconsidered further. Approximately 1350genes are differentially expressed in ins-lflies, 755 of which were found to have ho-mology with human genes using theGenomic Information for Eukaryotic Or-ganisms Database (www.eugenes.org).The mean, SEM, fold change, and both thecorrected and noncorrected p values for all1350 genes can be found in supplementalTable 2, available at www.jneurosci.org assupplemental material.

To further evaluate the 1350 genes thatwere differentially expressed between Cs andins-l flies, we conducted a GO analysis usingGOToolBox software (Martin et al., 2004)with the hypergeometric statistical method followed by false discov-ery rate correction. As seen in Figure 5A, over-represented GO cat-egories include metabolism, neuronal activity, behavior and sensoryperception. Changes in genes associated with lipid metabolism andsynapse transmission are consistent with the increased adiposity andlearning deficits observed in ins-l flies. Importantly, the overrepre-sentation of genes associated with sensory perception suggest thepossibility that hyperarousal in insomniacs may be attributable toincreased activity within sensory systems and that these processesmay be under genetic control.

The genes listed in supplemental Table 2, available at www.jneurosci.org as supplemental material, were identified from

three experimental replicates collected on separate days. Giventhat the expression data were further analyzed using two inde-pendent statistical approaches with extremely conservative ad-justments for multiple tests, we believe the results to be reliable.Nonetheless, we collected a fourth independent replicate of theshortest-sleeping ins-l flies and normal-sleeping Cs flies for con-firmation using QPCR. As above, flies were monitored for 3 d toensure that sleep was stable, and the flies were collected at ZT3.Genes were rank ordered by p value and QPCR confirmation wasconducted on candidate genes that fell within the top 0 –5%,5–50%, and bottom 50% of all genes. As seen in Figure 5B, wesuccessfully confirmed expression changes across all levels of sig-

Figure 5. Gene expression in ins-l flies. A, GO categories identified using GOToolBox software schematic. Note the overrepre-sentation of genes involved in sensory perception. Nb in set, Number of genes differentially expressed for the corresponding theGO category; Freq, number of genes with the corresponding GO annotation divided by the total number of GO-annotated genesdifferentially expressed. B, QPCR confirmation of gene expression changes in short-sleeping ins-l flies expressed as fold changefrom normal-sleeping Cs controls. RNA was collected from all flies after 3 h of spontaneous waking at ZT3. Genes were rank orderedby p value, and confirmation was conducted on the top 5% (black), 5–50% (gray), and bottom 50% (white) of all genes. Thickarrow indicates confirmation of Amylase expression. Error bars represent SEM.


nificance, providing further validation that the identified genesare modified in ins-l flies.

If these genes are associated with the insomnia phenotypes,their expression should persist even when ins-l flies are placedinto a different genetic background. Although we do not yet havea genetic marker for the ins-l flies, our results indicate that ins-l isdominant (Fig. 1F). Thus, ins-l flies were out-crossed to normallysleeping w1118 flies. After each cross, white-eyed progeny thatdisplayed short-sleep, short-sleep bouts, and hyperactivity wereidentified and then crossed again to normal-sleeping w1118 flies.This was repeated five times, creating a new stock, ins-lw. ins-lw

flies were then divided into two groups and selected again for 20generations: one group was reselected to amplify insomnia-likephenotypes, whereas the other was back-selected to obtainnormal-sleeping flies (nsw flies) (supplemental Fig. 1, available atwww.jneurosci.org as supplemental material). Sleep time wasmodestly increased in ins-lw flies immediately after the outcrossbut returned to typical ins-l levels within three rounds of selectionand remained stable thereafter, indicating that the critical lociwere maintained in this new line (data not shown). Importantly,ins-lw flies exhibited all of the phenotypes found in ins-l flies.After the reselection, we performed real-time QPCR on headRNA extracts obtained from ins-lw and normal-sleeping nsw fliesfor a subset of the genes shown in Figure 5B. As above, flies weremonitored for 3 d to ensure sleep stability, and RNA was collectedat CT3. As seen in supplemental Figure 1B, available at www.jneurosci.org as supplemental material, the expression changesseen in ins-lw versus nsw are similar to that observed in ins-l versusCs flies. Thus, genes associated with insomnia can be identified inat least two different genetic backgrounds.

Genes differentially regulated ins-l flies are modulated bysleep loss in humansAn important issue about Drosophila sleep research is whether ithas relevance for human sleep research. We have previouslyshown that Amylase, a biomarker of sleepiness in Drosophila, isupregulated in human saliva after sleep loss (Seugnet et al., 2006).Amylase is not responsive to stress in flies and is only transientlyelevated by stress in humans (Takai et al., 2004; Seugnet et al.,2006; Schoofs et al., 2008). Importantly, we demonstrated thatAmylase levels were elevated after 28 h but not 24 h of waking inhumans, whereas cortisol levels remained unchanged (Seugnet etal., 2006). Thus, it is possible to identify genes in human salivathat are responsive to sleep loss. Saliva contains thousands ofmRNAs, and recent studies have demonstrated that they can beused as diagnostic markers for human diseases (Palanisamy et al.,2008). To determine whether genes identified in ins-l flies couldbe modified by sleep disruption in humans; we designed primersfor the human homologues of six genes differentially expressed inins-l flies. Of these six genes, only two, malic enzyme (homolog ofDrosophila men) and Filamin A (homolog of Drosophila cheerio),are reliably detected by QPCR in saliva RNA extracts. men andcheerio have elevated mRNA levels in ins-l flies (Fig. 6A). Inter-estingly, their human homologues are upregulated in normalsubjects after 28 h of waking, indicating that both genes are mod-ulated by sleep loss in humans and flies (Fig. 6B).

DiscussionUsing artificial selection, we have generated a unique line of fliesthat exhibit a constellation of stable and heritable phenotypesthat are directly relevant for addressing fundamental questionsabout sleep regulation. These flies display large disruptions insleep and as a consequence can be useful in identifying basic

mechanisms of sleep regulation. Importantly, the sleep deficitsobserved in ins-l flies are not produced by mechanical interven-tions. Thus, these flies are well suited to evaluate the acute andlong-term consequences of sleep disruption at all levels of inves-tigation, including genetic, circuit, physiologic, and behavioralanalyses. Our exhaustive characterization of ins-l flies indicatesthat they may be particularly useful for providing additional in-sight into mechanisms linking sleep with important physiologicalprocesses underlying metabolism, learning, and aging.

An additional and important feature of the ins-l flies is that thechanges in behavior are unlikely to be caused by changes in asingle gene. The fact that 30 generations were necessary to reach aplateau in the selection process suggests that a large number ofgenes are involved in the ins-l phenotype. Interestingly, a similarnumber of generations (20 –30) allowed the progressive selectionof other complex behaviors such as learning (Mery and Kawecki,2002), locomotion (Jordan et al., 2007), or aggression (Dierickand Greenspan, 2006). In addition, we selected for multiple phe-notypes, each of which exhibited slow incremental changes overthe course of many generations. Thus, it is unlikely that we inad-vertently selected for a mutation at a single locus. Rather, the ins-lphenotypes are undoubtedly a consequence of individuals inher-iting many alleles which exert small but cumulative effects onsleep regulatory circuits (Mackay et al., 2005). This interpretationis consistent with the observation that it is rare for sleep disordersto be attributed to single gene defects (Tafti et al., 2005). Thus,ins-l flies more closely approximate conditions found in humanpopulations, further increasing the utility of these animals for theefficient dissection of sleep regulation.

We chose to create an animal model of insomnia based on ourhypothesis that sleep disorders are highly prevalent in generalpopulations because of the inherent complexity of sleep regula-tion. Insomnia is among the most common of all sleep disorders.As a complaint, insomnia occurs in 30 –50% of the populationannually; when accompanied by daytime impairment, insomniaafflicts 9 –15% of the population, and when diagnosed usingDSM-IV criteria, the prevalence is 6% (Ohayon, 2002). Twinstudies suggest that genetics may account for approximately one-third of the variance in insomnia complaints (Heath et al., 1990;Watson et al., 2006). If insomnia results, in part, from predispos-ing trait characteristics, it should be possible to amplify thesetraits using laboratory selection. Insomnia is defined as difficulty

Figure 6. Genes differentially regulated ins-l flies are modulated by sleep loss in humans. A,Filamin-A (Cheerio) and Malic enzyme (Men) are both upregulated in ins-lw flies compared withnsw flies. QPCR data from 20 fly heads collected at ZT0. Levels are expressed as percentage of nsw

expression. B, Filamin-A and Malic enzyme expressions are elevated after 28 h of waking inhumans (n � 8; Wilcoxon signed rank test, p � 0.02 and p � 0.059, respectively). QPCR dataobtained from saliva mRNA extracts. Each saliva sample collected after sleep deprivation wascompared with a circadian matched baseline sample from the same subject. Levels are ex-pressed as percentage of baseline expression. Error bars represent SEM.


falling asleep, difficulty staying asleep, or poor sleep quality whichis accompanied by daytime impairment or distress (Edinger et al.,2004). Moreover, patients with insomnia are hyperaroused andshow greater reactivity to stressors than good sleepers (Perlis etal., 2001; Bastien et al., 2008). With this in mind, we used artificialselection to generate flies with insomnia-like traits. Our selectioncreated flies with a tenfold reduction in sleep time. In addition,these flies exhibited (1) difficulty in initiating sleep as defined byincreased sleep latency; (2) difficulties in maintaining sleep asindicated by an inability to maintain normal length sleep bouts;(3) hyperarousal, as measured by both an increase in locomotoractivity during waking and increased responsivity to environ-mental perturbations; (4) reduced lifespan; (5) decreased cogni-tive performance during the day; (6) evidence for increased sleepdrive during the animals’ primary wake period; and (7) difficultysleeping after abrupt changes to environmental zeitgebers. Toour knowledge, this is the first animal model of insomnia to resultin such large, stable, and heritable disruptions in sleep regulationthat are not brought about by experimentally induced stress.

Recently, several labs have used artificial selection coupledwith whole-genome arrays as an efficient strategy to identifygenes that underlie complex behavior (Dierick and Greenspan,2006; Edwards et al., 2006; Jordan et al., 2007; Sørensen et al.,2007; Zhou et al., 2007). Follow-up studies using single genemutations were then evaluated to demonstrate that the identifiedgene modified the behavior of interest in an otherwise wild-typebackground. One reason that no attempt was made to use genetictools to rescue the phenotypes observed in the selected lines isthat the behavior observed in these selected lines is likely attrib-utable to small changes in many genes. As a consequence, modi-fying a change in a single gene may not result in a large change inthe behavior in the selected lines. Thus, no gene has yet beenshown to be causally involved in producing the behavioral phe-notype in the selected flies themselves. Of course the goal of theselection strategy is to find genes whose function can be general-ized beyond an isolated and rare genetic line of flies. In thatregard, artificial selection combined with whole-genome geneprofiling has successfully identified candidate genes, many ofwhich have been shown to alter behavior using genetic strategies.

Using whole-genome arrays, we identified 1350 genes that aredifferentially expressed in ins-l flies compared with their genetic con-trols. The changes in gene expression are robust and were observedeven when ins-l was placed into a separate genetic background. ins-lflies are dominant, and thus, we were able to follow specificinsomnia-like traits over multiple crosses. The new line, ins-lw, dis-plays all of the characteristic traits found in ins-l flies, including thosethat were not actively selected during the outcross, such as an inabil-ity to sleep after the removal of zeitgebers. The observation that twogenes, which were identified in ins-l flies, are also responsive to acutesleep deprivation in humans increases our confidence that the genesidentified in the microarrays are robust and useful for investigatinggenes involved in sleep regulation.

It is important to acknowledge that all gene profiling experimentsare correlation in nature and thus identify genes that are causative fora given behavior and those that are consequence of the behavioralchange (Robinson et al., 2005). Thus, for each gene identified bytranscriptional gene profiling, genetic experiments are required todetermine whether the gene activation/inactivation reveals a path-way that regulates sleep, that is regulated by sleep, or that is part of acompensatory mechanism for sleep loss. This latter distinction isparticularly relevant for the ins-l flies. That is, although they displaysubstantial reduction in sleep in combination with cognitive impair-ments, increased adiposity, and reduced lifespan, ins-l flies also show

signs of resistance to the deleterious effects of waking. For example, asubstantial number of ins-l flies are able to remain continuouslyawake for several days without dying or showing overt signs of sick-ness. Interestingly, the longest-sleeping ins-l flies retain manyinsomnia-like traits, including severely fragmented sleep. Nonethe-less, they retain their ability to learn in the face of this challenge,whereas Cs flies with similarly fragmented sleep are learning im-paired (Seugnet et al., 2008). Although the changes in learning mayappear to be minor, they are well within the range of effect sizesobserved after sleep loss in humans and rodents across a number ofcognitive domains (Graves et al., 2003; Frey et al., 2004; Fu et al.,2007; Pierard et al., 2007). Together, these data suggest that bothsleep disruption and resilience to sleep loss are components of thegenetic condition and are likely to be reflected in gene expressionchanges.

Although we have identified a large number of candidategenes, our extensive phenotypic characterization of ins-l flies di-rects us toward specific classes of genes and neuronal circuits. Forexample, one of the most highly over-represented category ofgenes that are differentially modulated in ins-l flies is those in-volved in sensory perception. Thus, the increased amount ofwaking that is observed in ins-l flies may be due, in part, to thecontinued activity of specific sensory networks during sleep. Inthat regard, it is interesting to note that human insomniac pa-tients have also been hypothesized to display persistent sensoryprocessing during sleep as indicated by increased metabolism inthe thalamus (Nofzinger et al., 2004; Desseilles et al., 2008).

Given the established role of sleep in synaptic plasticity andthe learning deficits observed in ins-l flies, it is perhaps not sur-prising to find that another large class of over-represented genesin ins-l flies is involved in cell surface signaling (80 genes) orsynaptic transmission (30 genes). Interestingly, human insomni-acs show deficits in specific brain structures involved in memoryand behavioral flexibility (Nofzinger et al., 2004; Riemann et al.,2007). Similarly, specific structures involved in learning andmemory, such as dopaminergic neurons or the mushroom bodies(MBs), may play a key role in the deficit observed in ins-l flies.MBs regulate total sleep time and play an important role in pro-tecting flies from learning deficits after sleep deprivation (Joineret al., 2006; Pitman et al., 2006; Seugnet et al., 2008). Thus, theMBs are likely to play an important yet complex role in the cir-cuitry underlying insomnia. Finally, ins-l flies lose their ability tosleep after the removal of zeitgebers, suggesting that aspects ofinsomnia might involve specific subsets of clock neurons. Recentstudies have found that artificially increasing the electrical excit-ability of large ventral lateral neurons, which are responsive tolight, increases waking (Parisky et al., 2008; Shang et al., 2008;Sheeba et al., 2008). Although it is not clear whether more phys-iologic manipulations will produce similar results, genes affectingthis circuitry are of particular interest. Our data suggest that agene can play multiple roles in the brain, thereby producing anindividual that exhibits evidence of both sleep disruption andresilience to sleep loss. Identifying genes that confer resiliencemay provide crucial insight into mechanisms of sleep regulation.

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behavioral/systems/cognitive ... · flies were individually placed into 5 65 mm ... five flies aged...

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